Probing potassium in the atmosphere of HD 80606b with tunable filter transit spectrophotometry from the Gran Telescopio Canarias

Transcription

1 Mon. Not. R. Astron. Soc. 419, (2012) doi: /j x Probing potassium in the atmosphere of HD 80606b with tunable filter transit spectrophotometry from the Gran Telescopio Canarias Knicole D. Colón, 1 Eric B. Ford, 1 Seth Redfield, 2 Jonathan J. Fortney, 3 Megan Shabram, 1 Hans J. Deeg 4,5 and Suvrath Mahadevan 6,7 1 Department of Astronomy, University of Florida, Gainesville, FL 32611, USA 2 Astronomy Department, Van Vleck Observatory, Wesleyan University, Middletown, CT 06459, USA 3 Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064, USA 4 Instituto de Astrofísica de Canarias, C. Via Lactea S/N, La Laguna, Tenerife, Spain 5 Universidad de La Laguna, Department de Astrofísica, La Laguna, Tenerife, Spain 6 Department of Astronomy & Astrophysics, Pennsylvania State University, University Park, PA 16802, USA 7 Center for Exoplanets and Habitable Worlds, Pennsylvania State University, University Park, PA 16802, USA Accepted 2011 September 21. Received 2011 September 20; in original form 2010 August 13 ABSTRACT We report observations of HD using the 10.4-m Gran Telescopio Canarias and the Optical System for Imaging and low Resolution Integrated Spectroscopy (OSIRIS) tunable filter imager. We acquired very high precision, narrow-band photometry in four bandpasses around the K I absorption feature during the 2010 January transit of HD 80606b and during out-of-transit observations conducted in 2010 January and April. We obtained differential photometric precisions of for the in-transit flux ratio measured at nm, which probes the K I line core. We find no significant difference in the in-transit flux ratio between observations at and nm. Yet, we find a difference of 8.09 ± between these observations and observations at a longer wavelength that probes the K I wing ( nm). While the presence of red noise in the transit data has a non-negligible effect on the uncertainties in the flux ratio, the nm colour during transit shows no effects from red noise and also indicates a significant colour change, with a mean value of 8.99 ± This large change in the colour is equivalent to a 4.2 per cent change in the apparent planetary radius with wavelength, which is much larger than the atmospheric scaleheight. This implies the observations probed the atmosphere at very low pressures as well as a dramatic change in the pressure at which the slant optical depth reaches unity between 770 and 777 nm. We hypothesize that the excess absorption may be due to K I in a highspeed wind being driven from the exoplanet s exosphere. We discuss the viability of this and alternative interpretations, including stellar limb darkening, star-spots and effects from Earth s atmosphere. We strongly encourage follow-up observations of HD 80606b to confirm the signal measured here. Finally, we discuss the future prospects for exoplanet characterization using tunable filter spectrophotometry. Key words: techniques: photometric stars: individual: HD planetary systems. 1 INTRODUCTION Discoveries of extrasolar planets which transit their host star provide valuable opportunities to measure the physical properties of knicole@astro.ufl.edu NSF Graduate Research Fellow. exoplanetary atmospheres. The physical characteristics of an exoplanetary atmosphere can be probed by transmission spectroscopy observed against the spectrum of the host star. Seager & Sasselov (2000), Brown (2001) and Hubbard et al. (2001) developed models that predicted such absorption, particularly from Na I, K I and other alkali metals. Subsequent refinements of such models have confirmed that in the optical wavelength regime the strongest lines are expected from the Na I resonance lines (λλ589.6, nm) and C 2011 The Authors

2 2234 K. D. Colón et al. the K I resonance lines (λλ769.9, nm) (e.g. Barman 2007; Fortney et al. 2010). 1 In the optical, the cores of the atomic features of Na I and K I are relatively narrow. For this reason, medium to high resolution spectrographs can be used to compare the in-transit stellar spectrum to the out-of-transit (OOT) stellar spectrum. The absorption of stellar photons in the exoplanetary atmosphere leads to excess absorption in the in-transit stellar spectrum when compared to the OOT spectrum. In photometric observations, this leads then to deeper transits and a larger apparent size of the planet at the absorbing wavelengths (Brown 2001), with variations of order the atmospheric scaleheight (Fortney 2005). Such measurements in strong optical transitions can also constrain the atmospheric metallicity, rainout of condensates, distribution of absorbed stellar flux and photoionization of atmospheric constituents. The first detection of absorption due to an exoplanetary atmosphere came from Na I observations of HD b using the Space Telescope Imaging Spectrograph (STIS) onboard the Hubble Space Telescope (HST) (Charbonneau et al. 2002). Unfortunately, the subsequent failure of the STIS instrument prevented similar observations for more than 5 years. Thus, attention was directed towards making such observations from the ground (e.g. Moutou et al. 2001; Winn et al. 2004; Narita et al. 2005). The second detection of absorption due to an exoplanetary atmosphere, this time from the ground, was also made of Na I in observations of HD b using the 9.2-m Hobby Eberly Telescope (HET) (Redfield et al. 2008). Further detections of Na I in the atmosphere of HD b were made using archival data from the 8.2-m Subaru Telescope (Snellen et al. 2008), from HST by Sing et al. (2008a) and from Keck by Langland-Shula et al. (2009). The recent repair of STIS and installation of the Cosmic Origins Spectrograph (COS) onboard HST has enabled new optical and ultraviolet transmission spectrum observations of exoplanetary atmospheres, extended exospheres and auroral emission (e.g. Fossati et al. 2010; France et al. 2010; Linsky et al. 2010). Comparing the surprisingly weak Na I absorption in HD b (Charbonneau et al. 2002; Knutson et al. 2007) to the three times stronger Na I absorption of HD b (Redfield et al. 2008) suggests that the two planets have different atmospheric structures. Theorists have suggested numerous mechanisms such as adjustments to the metallicity, rainout of condensates, distribution of absorbed stellar flux or photoionization of sodium (Fortney et al. 2003; Barman 2007). In particular, Barman et al. (2002) suggested that non-local thermodynamic equilibrium Na level populations were the cause of the weak Na feature observed in HD b, and a reanalysis of the Knutson et al. (2007) data by Sing et al. (2008a,b) suggested that Na condensation or Na photoionization in HD b atmosphere was the best explanation for matching the data, given the Na line shapes they derived. It is clear that comparisons of the atmospheric properties of different transiting planets will be critical to understanding the atmospheric properties of exoplanets as a whole. Although still small, the list of detected atoms and molecules is growing. In addition to Na I, several molecules have been detected, primarily in the infrared, with both space-based and ground-based platforms, including CO, CO 2,H 2 OandCH 4 (Swain, Vasisht & 1 We caution that these lines are most prominent for hot Jupiter like planets with a certain range of atmospheric temperatures. Atmosphere models generated for HD 80606b at the time of transit [based on Fortney et al. (2010)] do not predict a significant K I absorption feature, due to the low equilibrium temperature of 500 K. We refer the reader to Section 4.4 for further discussion. Tinetti 2008; Swain et al. 2009; Snellen et al. 2010). Other HST observations using the Advanced Camera for Surveys (ACS) did not detect K I in HD b (Pont et al. 2008). If detections of constituents in the extended exosphere are included, then H I, CII, O I, MgII and other metals have also been detected (Vidal-Madjar et al. 2003, 2004; Fossati et al. 2010; Linsky et al. 2010). Each new detection provides not only compositional information, but also another window into the physical properties of the exoplanetary atmosphere (e.g. condensation, wind speed and photoionization). Even though atmosphere models do not predict a significant K I feature in HD 80606b, it remains of great interest to observationally determine the level of K I absorption in its atmosphere, since K I is generally predicted to be the second strongest transmission spectrum signature in the optical wavelength range. Further, Na I and K I probe different layers of the atmosphere. Measurements of K I can test the hypothesis that the low abundance of Na I on HD b may be due to a high-altitude layer of clouds or haze. Finding low abundance for both Na I and K I would be consistent with either the cloud hypothesis or with the photoionization hypothesis, as both are very easy to ionize. Finding that only Na I is significantly depleted would point to alternative models with complex atmospheric chemistry (e.g. incorporation into grains, odd temperature structure, unexpected mixing patterns). Finally, in principle, future observations could probe temporal variability of Na I and K I due to high-speed, high-altitude winds and/or differences in the leading and trailing limb (Fortney et al. 2010). All of the above atmospheric studies were based on observations using high-resolution spectrographs. Here, we describe a new technique that utilizes fast, narrow-band spectrophotometry with the Optical System for Imaging and low Resolution Integrated Spectroscopy (OSIRIS) installed on the 10.4-m Gran Telescopio Canarias (GTC) to probe the composition and other properties of the atmospheres of exoplanets that transit bright stars (see Section 2). Fast line spectrophotometry can be much more efficient (e.g. 34 per cent with GTC/OSIRIS) than typical high-resolution spectrographs ( 1 2 per cent) thanks to the use of a tunable filter (TF) rather than diffraction gratings. Further, this technique has the potential to be less sensitive to several systematic noise sources, such as seeing variations that cause line variations in wide spectrograph slits (specifically in non-fibre fed spectrographs), atmospheric variations (since reference stars will be observed simultaneously) and/or flat-fielding errors (since on- and off-line data are obtained at the same detector location). Thus, spectrophotometry with a TF technique is particularly well suited for observing a narrow spectral range of atomic absorption features, without suffering from the inefficiencies or potential systematic uncertainties of high-resolution spectrographs. Here we present results of such observations of the 2010 January transit of HD 80606b using the GTC and the OSIRIS TF imager. HD 80606b was originally discovered by radial velocity observations (Naef et al. 2001) and was remarkable due to its very high eccentricity (e = 0.93). Only several years later did Spitzer and ground-based observations reveal that the planet passes both behind and in front of its host star (Fossey, Waldmann & Kipping 2009; Garcia-Melendo & McCullough 2009; Laughlin et al. 2009; Moutou et al. 2009). Spectroscopic observations revealed that the angular momentum axis of the stellar rotation and that of the orbital planet are misaligned (Moutou et al. 2009; Pont et al. 2009; Winn et al. 2009). Given the infrequent transits and long transit duration ( 12 h), follow-up observations are quite challenging. Winn et al. (2009), Hidas et al. (2010) and Shporer et al. (2010) were able to characterize transits of HD 80606b with longitudinally distributed

3 Probing the atmosphere of HD 80606b 2235 networks of ground-based observatories, and Hébrard et al. (2010) observed the 2010 January transit using the Spitzer spacecraft. The Spitzer observations constrain the thermal properties of the planet s atmosphere (Laughlin et al. 2009; Hébrard et al. 2010). To the best of our knowledge, the observations presented here are the first to attempt to detect atmospheric absorption by HD 80606b. While existing atmosphere models predict that HD 80606b would not have any significant K I feature due to its high surface gravity and cold atmosphere at the time of transit (e.g. see Section 4.4), our observations test this prediction. Even though models do not predict a K I feature, exoplanet observations have a track record of unexpected discoveries. Furthermore, in principle, depending on the atoms/molecules found in the atmosphere, these observations could yield information about how the planet cools, independent of any observations of the thermal phase curve of this system. In principle, transmission spectroscopy also provides a way to characterize transiting planets in eccentric orbits, which either do not pass behind their host star or which are too cool to detect via occultation when they do pass behind the star. Finally, we note that HD is one of the best systems for making very precise spectrophotometric measurements. HD is the brightest of the transiting planet host stars which have a comparably bright reference star very nearby ( 20 arcsec). Also, the long duration between the second and third points of contact ( 6 h) of HD 80606b provides time to collect a large amount of in-transit data in a single transit. Thus, we expect that all else (e.g. observing conditions) being equal, HD 80606b permits the most precise spectrophotometric measurements of any known system (at least with observations of a single transit). This paper presents extremely precise measurements of the variation in HD 80606b s apparent radius with wavelength near the K I feature, which in turn can help us test the predictions of atmosphere models. Section 2 describes our observations and data analysis procedures. We describe the results of our observations in Section 3. In Section 4 we interpret the results, and we summarize our conclusions and discuss the future prospects for the method in Sections 5 and 6. 2 OBSERVATIONS HD and its nearby companion (HD 80607) are both bright G5 dwarves of a similar magnitude (V 9) and colour. On three nights, we measured the flux of both HD (target) and HD (reference) simultaneously. We cycled through a set of four wavelengths throughout the observations. On the night of 2010 January 13 14, the planet was in transit for the duration of our observations, and we measure an in-transit flux ratio of HD to HD for each wavelength. We repeated the observations on 2010 January 15 and 2010 April 4, when the planet was not transiting HD 80606, allowing us to measure the OOT flux ratio of HD to HD for each wavelength. Our results (Section 3) are based on the ratio of in-transit flux ratio (target over reference) to OOT flux ratio (target over reference). Any changes in the Earth s atmosphere from one night to the next should affect both the target and reference star similarly. By making differential measurements of the colour during the same transit and at similar atmospheric conditions, this method allows for extremely precise measurements of the transit depth at different wavelengths. While night-to-night variability in the atmospheric conditions or either of the stars could cause a systematic scaling of the transit depth measurements, the relative wavelength dependence of the apparent planet radius is largely insensitive to either of these potential systematics. We refer the reader to Sections and for further discussion. 2.1 In-transit and out-of-transit observations We observed a partial transit of HD 80606b on 2010 January and acquired baseline data on 2010 January 15 and 2010 April 4 to establish the OOT flux ratios. For our observations, we used the TF imaging mode of the OSIRIS instrument installed on the 10.4-m GTC, which is located at the Observatorio del Roque de los Muchachos on the island of La Palma (Cepa et al. 2000, 2003). In the TF mode, the user can specify custom bandpasses with a central wavelength of nm and a full width at half-maximum (FWHM) of nm. The effective wavelength decreases radially outward from the optical centre; because of this effect, we positioned the target and its reference star at the same distance from the optical centre and on the same CCD chip. The observed wavelengths described below refer to the location of the target (and reference) on the CCD chip. During the transit observations and baseline observations on 2010 January 15, exposures of the target and its reference star cycled through four different wavelengths (all with a FWHM of 1.2 nm): one on the predicted core of the K I line ( nm); one to the blue side ( nm) and two redwards of the K I feature ( and nm). As the tunings for the TF are set by the order sorter (OS) filter used, our bluest wavelength is the bluest wavelength we could observe at in the wing of the K I line and still observe within the same OS filter as the on-line wavelength (i.e. at the location of the core of the K I line). We then chose two wavelengths redwards of the K I line in order to sample more of the structure/wings around the K I line. The reddest bandpass was chosen since we expect to see (for a typical hot Jupiter) a maximum difference between the flux ratio in the on-line bandpass and around that reddest bandpass. In order to maximize the signal-to-noise ratios in the on-line wavelength and in the reddest off-line wavelength, in each sequence we observed on-line three times, at the reddest off-line wavelength two times and at the other off-line wavelengths one time each. During the transit, the observing sequence from the GTC was as follows: , , , , , and nm (repeat). We emphasize that these wavelengths were chosen to be around the location of the K I feature in HD 80606b s atmosphere. In order to observe on the K I feature (which has a rest wavelength of nm) in the frame of the planet, we accounted for the Doppler shifts due to the Earth s motion around the Sun, the system s radial velocity and the planet s non-zero radial velocity during transit [ 59.6 km s 1 based on velocities from Winn et al. (2009)]. After accounting for these effects, the observed wavelengths in the frame of the planet are redshifted by 0.16 nm to nm (on-line) and , and nm (off-line). The observed wavelengths in the frame of the star are essentially the same as observed on Earth due to the small systemic velocity of the HD planetary system and the Earth s small barycentric velocity on the night of the transit. For the remainder of the paper, we report the wavelengths as observed in the frame of the planet when discussing results from the transit observations. A similar sequence as described above was used for the baseline observations taken on 2010 April 4, but the observed wavelengths were corrected for the Doppler shift due to the planet s orbital velocity on that specific date ( 23.9 km s 1 )inordertomatchthe wavelengths observed during the transit. Thus, the wavelengths observed on 2010 April 4 (from the GTC) are nm (on-line) and , and nm (off-line).

4 2236 K. D. Colón et al. Transit observations of HD 80606b began at 22:28 UT on 2010 January 13 (during ingress) and ended at 7:15 UT on 2010 January 14 (around the beginning of egress and including astronomical twilight), during which the airmass ranged from 1.08 to The observing conditions were photometric, with a clear sky and a dark moon. No data were taken between 5:20 and 5:50 UT on 2010 January 14 due to recalibration of the TF during that time. The actual seeing varied between 0.7 and 0.9 arcsec during the transit observations, but we used a slight defocus to increase efficiency and reduce the impact of pixel-to-pixel sensitivity variations. Therefore, the defocused FWHM of the target varied from 0.9 to 2.3 arcsec (7 18 pixels) during the transit. For the portion of the light curve used in our analysis (see Section 2.2), the FWHM was much more stable than is indicated by the range given above, with a typical value between 10 and 14 pixels and a mean value of 12 pixels. Even with an autoguiding system, the target s centroid coordinates shifted by 9 10 pixels over the course of the night. We used 1 1 binning and a fast readout mode (500 khz) to readout a single window of pixels (located on one CCD chip) in order to reduce the dead time between exposures. This window is equivalent to a field of view of arcsec 2, so the only stars in our field were HD and a single reference star, HD Each individual observation was followed by an average dead time of less than 4 s for readout and to switch between TF tunings. We used 10-s exposures, resulting in an overall cadence of about 14 s for each observation. Due to the short exposure time used, the sky background level was low enough that we did not need to discard any images taken during astronomical twilight. Baseline observations were taken from 5:50 to 7:10 UT (i.e. also through the beginning of astronomical twilight) on 2010 January 15, but the data were highly scattered, so we do not include it in our primary analysis. 2 Additional baseline observations took place on 2010 April 4 from 21:30 (including the end of astronomical twilight) to 0:00 UT. The observing conditions were photometric and taken during grey time, using the same set-up as the in-transit observations described above. During the observations, the airmass ranged from 1.08 to 1.20, and the actual seeing varied between 1.4 and 1.6 arcsec ( pixels), so the telescope was not intentionally defocused. The target s centroid coordinates shifted by 5 8 pixels during the observations. The exposure time was changed from the initial exposure time of 10 s to 8 s and then again to 11 s to counteract variations in the seeing as well as increasing airmass while avoiding saturation and maintaining a high number of counts. In our analysis, we discard the 10-s data because a majority of the images were saturated. We tested using the OOT flux ratios from the 8 and 11 s data individually in our analysis and found that they produced very similar results. Thus, we combine the 8 and 11 s data to establish the final OOT flux ratios (see Section 2.2) and to achieve the longest usable baseline possible. 2.2 Data reduction and analysis Observations taken with OSIRIS prior to 2010 mid-march suffered from a higher than expected level of dark current despite the short exposure times used. Therefore, we used standard IRAF procedures for bias and dark subtraction and flat-field correction for the 2010 January transit observations of HD We note that the flatfields for these observations did not produce the pattern of having the total number of counts in the dome flat-fields decreasing with Table 1. Absolute transit photometry from 2010 January 13. λ (nm) HJD F target F ref Note. The wavelengths included in the table are the observed wavelengths in the frame of the planet (see text for additional details). The time stamps included here are for the times at mid-exposure. F target and F ref are the absolute flux measurements of HD and HD The full table is included online (see Supporting Information), while a portion is shown here so the reader can see the formatting of the table. time as seen by Colón et al. (2010), so we use almost all (65 out of 75) dome flats for each observed wavelength in our analysis (the 10 dome flats not included in the analysis were overexposed). A new dewar fixed the problems with the dark current before the 2010 April observations took place, so for the baseline data we performed standard bias subtraction and flat-field correction (combining all 133 flats taken for each observed wavelength) and did not need to subtract dark frames. Because of the very small readout window used for our observations, our images do not contain the sky (OH) emission rings that occur due to the TF s small bandpass and position-dependent wavelength. Therefore, we performed simple aperture photometry on the target and reference star using the standard IDL routine APER 3 for a range of aperture radii. We measured the rms scatter of the flux ratio (equal to the target flux divided by the reference flux) at the bottom of the transit (for the 2010 January data) and for the individual 8 and 11 s data taken OOT (in 2010 April) in each bandpass. We considered the results for each bandpass and adopted an aperture radius of 28 pixels (3.6 arcsec) for the in-transit data and 32 pixels (4.1 arcsec) for the OOT data, as these were the aperture radii that typically yielded the lowest rms scatter. The radii of the sky annulus used for the reduction of both data sets were pixels in order to completely avoid any flux from the target or reference star. We have included the results of our aperture photometry in Tables 1 and 2 and illustrate the results in Figs 1 and 2. As illustrated, the flux in each bandpass displayed large variations during parts of the observations (particularly during parts of the transit), and we take this into consideration in our analysis (see Section 3.1). We present the raw in-transit light curves in Fig. 3, which were computed by dividing the flux in the target aperture by the flux in the reference star aperture and then normalizing by the weighted mean OOT flux ratio for each bandpass (see Section 3 for details on the computation of the mean flux ratios). In an attempt to reduce systematic trends seen in our transit light curves, we applied the external parameter decorrelation (EPD) technique (see e.g. Bakos et al. 2007, 2010) to each transit and baseline light curve. Note that for the transit light curve, we only applied EPD to the 4 h centred around mid-transit, or 3:36 UT on 2010 January 14, as estimated by 2 See Section 4.2 for further discussion of this data set. 3 Landsman 1993;

5 Probing the atmosphere of HD 80606b 2237 Table 2. Absolute OOT photometry from 2010 April 4. λ (nm) t exp (s) HJD F target F ref Note. Columns are similar to Table 1, except the wavelengths included in the table are the wavelengths as observed from the GTC (see text for additional details). The second column contains the exposure time for the observations, as observations based on two different exposure times were included in our analysis. The full table is available online (see Supporting Information), and a portion is shown here so the reader can see the formatting of the table. Figure 2. Similar to Fig. 1, but for the OOT data taken the night of 2010 April 4. Note that the discontinuity in the fluxes around is due to a change in the exposure time (from 8 to 11 s). Figure 1. Absolute fluxes of HD (a) and HD (b) as measured on 2010 January The different light curves represent the fluxes as measured nearly simultaneously in the different bandpasses, with the black, blue, brown and red light curves representing the , , and nm data. These data have not been corrected for airmass or decorrelated in any way. Note the break in the data around 2 h after midtransit due to recalibration of the TF. The vertical solid lines indicate the expected beginning and end of the transit, and the vertical dotted lines indicate the end of ingress and the beginning of egress [based on durations estimated by Hébrard et al. (2010) and the transit ephemeris from Shporer et al. (2010)]. The vertical dashed lines indicate the 4h interval around mid-transit that our analysis focused on (see text for further details). Shporer et al. (2010). 4 Specifically, we decorrelated each individual light curve against the following parameters: the centroid coordinates of both the target and reference, the sharpness of the target and reference profiles [equivalent to (2.35/FWHM) 2 ] and the airmass. As illustrated in Fig. 4, EPD removed most of the correlations in the in-transit data. For reference, we show the correlations between the in-transit data and the target s FWHM and centroid coordinates both before and after EPD has been applied in Fig. 5. For the baseline data, we performed EPD for the 8- and 11-s data series separately, but we then combined the two data sets to compute the weighted mean flux ratio and its uncertainty for each bandpass as described 4 This ephemeris is in between that given by Winn et al. (2009) and Hébrard et al. (2010). The choice of ephemeris used does not significantly affect our results. Figure 3. Transit light curves as observed nearly simultaneously in different bandpasses on 2010 January The on-line light curve ( nm) is shown in black, and the off-line light curves (768.76, and nm) are shown in blue, brown and red. The flux ratio for each bandpass has been normalized to the weighted mean OOT flux ratio estimated from the baseline data acquired in 2010 April, but the data have not been corrected for airmass or decorrelated in any way. The off-line light curves have been arbitrarily offset by 0.006, and 0.018, and error bars are not shown for clarity. The vertical solid, dotted and dashed lines are the same as in Fig. 1. in Section 3. The results of the decorrelation for the OOT data are illustrated in Fig. 6. As a result of applying EPD, the rms scatter in each of the bandpasses improved by as much as 25 per cent, but decorrelating the light curves against the above parameters did not completely remove the systematics that are seen in our data. In a further attempt to remove systematics, we also tried a quadratic decorrelation against the sharpness of the target and reference profiles, as that was the only parameter that showed a possible residual systematic pattern after EPD was applied. However, the quadratic decorrelation did not reduce systematics in our light curves any further. We discuss other potential sources of systematics in detail in Section 4.9.

6 2238 K. D. Colón et al. Figure 4. Relative in-transit flux ratio normalized to the relative OOT flux ratio as measured on 2010 April 4. The relative flux before (a) and after (b) EPD was applied is shown. The different colours represent the flux ratios as measured in the different bandpasses, with the colours the same as in Fig. 3. Note that EPD was only applied to the 4 h centred around mid-transit (i.e. the bottom of the transit light curve). The data shown have not been binned, but the different light curves have been offset arbitrarily for clarity. Because our goal is to compare the depths of the transit in each bandpass, the rest of our analysis focuses on the data from the bottom of the transit as presented in Fig. 3 and highlighted in Fig. 7 i.e. the 4 h centred around mid-transit. Note that the light curves shown in Fig. 7 have been corrected using EPD. We also discarded points that had a flux ratio greater than 3σ from the mean of the bottom of the transit light curve. This resulted in discarding four points from the reddest light curve ( nm). We also discarded several exposures from each wavelength that were unusable due to saturation. The different panels in Fig. 7 illustrate the deviation between the magnitude of the on-line flux ratios and each of the off-line flux ratios, which will be discussed in detail in Sections 3 and 4. We estimated the uncertainties in the flux ratios by computing the quadrature sum of the photon noise for HD and HD 80607, the uncertainty in the sum of the sky background (and dark current, for the in-transit observations) and the scintillation noise for the two stars. We assume Poisson statistics to compute the uncertainty in the sky background, and the noise due to scintillation was estimated from the relation given by Dravins et al. (1998), based on Young (1967). We caution that this empirical relation might overestimate scintillation for large telescopes located at excellent sites such as La Palma. Regardless, the relation demonstrates that scintillation is still a small contribution to the total error budget for these observations. The flat-field noise is also negligible compared to the photon noise, so we do not include it in our determination of the measurement uncertainties. Based on the relation given by Howell (2006), which computes the standard deviation of a single measurement in magnitudes and includes a correction term between the error in flux units and the error in magnitudes, we find the median total uncertainties in the flux ratio for each exposure to be 0.538, 0.532, and mmag at , , and nm (over the bottom of the transit), respectively. The rms of the transit light curve is comparable, but slightly larger, with values of 0.585, 0.667, and mmag for those wavelengths. The median total uncertainties for the OOT observations are calculated in a similar way, but the uncertainties for the 8- and 11-s data sets were scaled by the flux ratios for each respective set in order to compute a weighted uncertainty. Thus, the median total (weighted) Figure 5. Correlations between the normalized in-transit flux ratio and the target FWHM and x and y centroid coordinates, before (left-hand column) and after (right-hand column) EPD has been applied. All four bandpasses are shown in each panel, with the colours the same as in Fig. 3. Similar results were obtained when decorrelating the data against the reference parameters but are not shown here. Figure 6. Relative OOT flux ratio as measured on 2010 April 4. The relative flux before (a) and after (b) EPD was applied is shown. The different colours represent the flux ratios as measured in the different bandpasses, with the colours the same as in Fig. 3. Note the small break in the data around where the exposure time was changed. The data have not been binned, but the different light curves have been offset arbitrarily for clarity. uncertainties in the flux ratio are 0.657, 0.650, and mmag, while the estimated rms is quite comparable, with values of 0.562, 0.605, and mmag for , , and nm, respectively.

7 Probing the atmosphere of HD 80606b 2239 Table 4. Normalized photometry from around mid-transit. λ (nm) HJD F ratio F ratio Uncertainty (raw) (corrected) Note. The wavelengths included in the table are the observed wavelengths in the frame of the planet (see text for additional details). The time stamps included here are for the times at mid-exposure. The flux ratios are presented both before (raw) and after (corrected) EPD was applied. The flux ratios have also been normalized to the weighted mean OOT flux ratio (see Table 6 and text for more details). The full table is available online (see Supporting Information), and a portion is shown here so the reader can see the formatting of the table. Table 5. Relative OOT photometry from 2010 April 4. λ (nm) t exp (s) HJD F ratio F ratio Uncertainty (raw) (corrected) Figure 7. Corrected light curves for observations of the bottom of the transit as observed nearly simultaneously in different bandpasses on 2010 January In each panel, the black points illustrate the measurements taken in the on-line ( nm) bandpass. We also show measurements taken in each of the off-line bandpasses (768.76, , nm) in each of the respective panels (a, b, c) for comparison to the on-line flux ratios. The data shown here have been decorrelated. The colours and normalizations are the same as in Fig. 3, but no offsets have been applied. Here, we have binned the data and error bars simply for clarity. Table 3. Relative transit photometry. λ (nm) HJD F ratio Uncertainty Note. The wavelengths included in the table are the observed wavelengths in the frame of the planet (see text for additional details). The time stamps included here are for the times at mid-exposure. F ratio represents the relative flux ratio between the target and reference star (i.e. F target /F ref ). The full table is available online (see Supporting Information), and a portion is shown here so the reader can see the formatting of the table. The complete photometric time series for each bandpass of the in-transit data (uncorrected and unnormalized) is reported in Table 3, while the photometric time series (both before and after EPD was applied) for the transit bottom and the April observations are reported in Tables 4 and 5. The weighted mean flux ratios for both the in-transit and OOT data (see Section 3 for more details) are given in Table 6, along with their uncertainties Note. The wavelengths included in the table are the wavelengths as observed from the GTC (see text for additional details). The time stamps included here are for the times at mid-exposure. The flux ratios are presented both before (raw) and after (corrected) EPD was applied. The full table is available online (see Supporting Information), and a portion is shown here so the reader can see the formatting of the table. 3 RESULTS As illustrated in Fig. 7, we can see by eye a hint of a deviation between the in-transit flux ratios observed at the on-line wavelength and the red off-line wavelengths, but no clear deviation is seen when compared to the bluest off-line wavelength. Despite evidence of time-correlated systematics in our data, we emphasize that the error bars shown in Fig. 7 are binned error bars, which illustrate that our measurement uncertainties are larger than any residual systematics present in the light curves and that the deviations in the flux ratios between the different bandpasses are real. We refer the reader to our discussion of possible systematic sources in Section 4.9. In Fig. 8, we plot histograms of the (unbinned) flux ratios at the bottom of each of the transit light curves, where the flux ratios have been normalized against the mean OOT flux ratio for each respective wavelength. These histograms further illustrate that the flux ratios for the on-line and bluest off-line light curves are comparable, but the red off-line flux ratios (particularly for the reddest light curve) clearly lie at slightly higher values compared to the on-line flux ratios, indicating a smaller apparent planetary radius at those wavelengths. Ideally, when one has access to either a complete or partial transit light curve and baseline data acquired immediately before or after

8 2240 K. D. Colón et al. Table 6. Time-averaged flux ratios and noise estimates. λ E (nm) λ P (nm) λ S (nm) δf/f σ δf/f σ w σ r β In-transit Out-of-transit Note. λ E is the observed wavelength from the GTC (i.e. from the Earth), λ P is the observed wavelength in the frame of the planet and λ S is the observed wavelength in the frame of the star. Values for λ P are not given for the OOT observations, as the planet was not transiting and was therefore not technically observed. The in-transit ratios refer to the relative flux ratio between the target and reference that has been normalized to the weighted mean OOT flux ratios (given at the bottom of the table). Figure 8. Histograms of normalized flux ratios from the bottom of the transit light curve as shown in Fig. 4(b). The histograms were generated using a bin size of 0.5 mmag. Each panel compares the on-line flux ratios with the off-line flux ratios. In each panel, the black (solid) histograms represent the nm (on-line) light curve. The blue (dotted), brown (dashed) and red (dot dashed) histograms are for the , and nm light curves and are shown in panels (a), (b) and (c), respectively. Panel (d) shows the histograms for all four wavelengths for further comparison. the transit event, one can fit a model to the data and estimate the transit depth from the model results. Due to the very long duration of HD 80606b s transit, we were not able to acquire baseline data on the night of the transit, thereby making this type of analysis impractical. However, thanks to several recent campaigns to observe a complete transit of HD 80606b and establish accurate orbital and physical parameters for this system via light-curve modelling (Winn et al. 2009; Hébrard et al. 2010; Hidas et al. 2010; Shporer et al. 2010), we do not need to fit a model to our partial light curve to achieve the goals of this paper. Instead, we consider only the middle 4 h of the transit light curve in our analysis (compared to the full duration of the bottom of the transit, which is 6 h), thereby minimizing systematic effects of stellar limb darkening (LD) as the strongest LD occurs during ingress, egress and right after/before ingress/egress. Further, since we do not know the LD model for this star to the precision of our observations, adding such a model would not be useful for this study. Thus, we assume that LD is the same over all our bandpasses and that the transit ephemeris, impact parameter and transit duration do not vary with wavelength. The only parameter of which we assume changes with wavelength is the apparent planet radius (R p ). To investigate how the apparent planet radius changes with wavelength, we simply compute the weighted mean in-transit flux ratio [ δf/f, which is proportional to the planet-to-star radius ratio, (R p /R ) 2 ], and its uncertainty for each wavelength. Specifically, we compute the weighted mean as n w i F i i=1 δf/f =, (1) n w i i=1 where the weights, w i,areequalto1/(βσ i ) 2. Here, σ i is the estimated photometric uncertainty weighted by some wavelengthspecific factor (β) in order to account for the presence of any red noise in each individual bandpass. To illustrate the effect of red noise on our measurements and the need for a re-weighting factor, the standard deviations (σ N )of the in-transit and OOT time-binned flux ratios are shown in Figs 9 and 10 as a function of binning factor (N) for each bandpass. The theoretical trend expected for white Gaussian noise ( N 1/2 )is plotted as a solid curve, and we can see that for the in-transit data the rms deviates from the theoretical curve at large binning factors, indicating that red noise is present in most bandpasses (being the least significant in the bluest bandpass). However, for the OOT data, our photometry appears to be generally consistent with the photon limit (although the bluest light curve suffers from small number statistics). Following methods used by e.g. Pont, Zucker & Queloz (2006) and Winn et al. (2007), we calculated explicit estimates for both the white (σ w )andred(σ r ) noise in each bandpass by solving the following system of equations: σ 2 1 = σ 2 w + σ 2 r (2) σ 2 N = σ 2 w N + σ 2 r. (3)

9 Probing the atmosphere of HD 80606b 2241 Figure 9. Standard deviation of the time-binned flux ratio measurements from the bottom of the transit [e.g. as shown in Fig. 4(b)] as a function of the number of data points per bin (N). Panels (a), (b), (c) and (d) show the standard deviations for the binned , , and nm light curves. The amount of binning that could be performed varies for each light curve since the different wavelengths were observed a different number of times in a given observing sequence (see Section 2.1, for details). The solid line in each panel represents the trend expected for pure white Gaussian noise ( N 1/2 ), normalized to the unbinned standard deviation measured in our data. The dotted lines represent the trend for Gaussian noise when normalized to the theoretical noise for our observations. The dashed curves are models fitted to the standard deviation that include both white and red noise. The effect of red noise is obvious in all bandpasses. The re-weighting factor, β, is then computed as σ r /(σ w / N). Based on our fits to the red and white noise, we computed a re-weighting factor for each bandpass and applied it as stated above. We imposed a minimum value for β of 1, particularly for cases where red noise was negligible. The uncertainties for the OOT flux ratio are also weighted by the flux ratio, F i, since two different exposure times were used during the OOT observations. Finally, the uncertainty on the weighted mean is computed as 1 σ δf/f =. (4) n w i i=1 We include the uncertainty on the weighted mean OOT flux ratio in our calculation of the mean normalized in-transit flux ratio and its uncertainty. The resulting spectrum of HD 80606b (the normalized weighted mean in-transit flux ratios as a function of wavelength) is shown in Fig. 11, and it clearly illustrates a difference between the flux ratios for the bluest bandpasses and those for the reddest bandpasses. While we find no significant difference between the flux ratios measured at and nm, we measure differences of 3.02 ± and 8.09 ± between observations at and and nm. We list the weighted mean in-transit flux ratios (normalized by the weighted mean OOT flux ratios) as well as the weighted mean OOT flux ratios and their uncertainties in Table 6. In this table, we also include our fits to the white and red noise, as well as our estimates for β. When calculating the normalized in-transit flux ratio and its uncertainty, we also included the re-weighted uncertainty for the Figure 10. Standard deviation of the time-binned OOT flux ratio measurements from 2010 April [e.g. as shown in Fig. 6(b)] as a function of the number of data points per bin (N). Panels (a), (b), (c) and (d) show the standard deviations for the binned , , and nm light curves. The solid line in each panel represents the trend expected for pure white Gaussian noise ( N 1/2 ). The dotted lines represent the trend for Gaussian noise when normalized to the theoretical noise for our observations. The dashed curves are models fitted to the standard deviation that include both white and red noise. Compared to the in-transit observations, red noise has a very minimal effect here. Deviations below the curve are likely due to small number statistics. These results demonstrate that narrowband ground-based observations can provide very high precision differential photometry. For a given bandpass, the combined precision exceeds that of Spitzer (Hébrard et al. 2010) or HST observations (Pont et al. 2008). To the best of our knowledge, these represent the highest precision photometry for a 1.2-nm bandpass for ground or space observations. mean OOT flux ratio in our calculation. The error bars for the flux ratios given in Table 6 and shown in Fig. 11 also take red noise into account. 3.1 Effects of Earth s atmosphere We consider the effect of random atmospheric variations (e.g. clouds) during the night of the transit as well as during the April baseline observations. As mentioned in Section 2.2, large variations in the absolute flux of both the target and reference were observed towards the beginning and the end of the transit observations, with a few large fluctuations around the middle of the observations as well. Thus, to check if our measured in-transit flux ratios were affected by these fluctuations, we computed the weighted mean in-transit flux ratio for each bandpass after excluding outlying absolute flux measurements from our analysis. We specifically excluded any points that were greater than 3σ away from the mean of the flattest part of the spectrum measured for each bandpass and each star. After excluding outlying points from both the in-transit and April baseline data, we found that the new spectrum for HD 80606b shows a very similar shape as the original spectrum, albeit with the flux ratio in the reddest bandpass differing the most from the original spectrum. However, we still measure a significant difference between the flux ratios in the on-line and reddest bandpasses. These resultsareincludedintable7andshowninfig.11asthesolid circles.

10 2242 K. D. Colón et al. Figure 11. Normalized weighted mean in-transit flux ratio versus observed wavelength (in the frame of the planet). The open triangles represent the flux ratios as computed for each light curve described in Sections 2 and 3. The solid circles represent the flux ratios computed after excluding outlying absolute flux values for each star from the analysis (see Section 3.1). Note that the solid circles have been offset by 0.25 nm for clarity. The vertical error bars include a factor to account for the effects of red noise in both the in-transit and OOT data. The error bars in the horizontal direction indicate the FWHM of each bandpass. The solid squares represent the mean in-transit flux ratios estimated from limb-darkened transit light curve models for HD 80606b. The lines show the predictions of planetary atmosphere models (see Section 4.4, for more details). The inset figure shows the atmosphere models on a small vertical scale. While LD or night-to-night variability (of Earth s atmosphere or either star) could affect the overall normalization, the observed change in the flux ratio with wavelength is robust. 3.2 Limb-darkening effects So far our analysis has assumed that LD is the same between our different bandpasses, so LD should not affect the mean flux ratios for each bandpass differently. However, in principle, there is also the possibility that LD coefficients vary significantly in and out of narrow spectral lines. To investigate the possibility that our spectrum s signature is a result of our probing in and out of HD s stellar spectral lines, we have computed quadratic LD coefficients for each of our bandpasses for a grid of stellar models [using PHOEBE;Prša & Zwitter (2005)]. We then generated theoretical limb-darkened light curves for each bandpass using the standard planet transit model of Mandel & Agol (2002). We used stellar parameters and uncertainties for HD as given by Winn et al. (2009) to estimate a range of LD coefficients to use in our models. We also input planetary parameters and uncertainties for HD 80606b as given by Hébrard et al. (2010). After computing light-curve models for different combinations of LD coefficients and planetary parameters, we computed the mean model flux ratio over the bottom of each transit light curve (the 4 h centred around mid-transit). We include the resulting model spectrum in Fig. 11 as solid squares. This particular spectrum was computed based on using a median set of LD coefficients, but all the model results were similar over the range of LD coefficients used. The median linear and quadratic LD coefficients (u 1, u 2 )are (0.392,0.229), (0.388,0.233), (0.391,0.230) and (0.376,0236) for the , , and nm bandpasses. While small differences in LD exist between the different bandpasses, the mean model flux ratios differed by only a very small amount (< ) between the different bandpasses. From this, we conclude that LD is most likely not the cause of the large variations in our observed spectrum. However, we note that PHOEBE (as well as other LD codes) has not been calibrated in and out of narrow spectral lines. We also note that the models show that the bottom of the light curve is in fact not flat due to LD. However, based on our calculation of the mean model flux ratio over the limb-darkened transit bottom for each bandpass, this should not affect the magnitude of the variations we measure in our observed spectrum. Due to LD effects, the overall normalization of the spectrum may be affected. 3.3 Transit colour In Fig. 12 we present the colour of the normalized in-transit flux ratios, computed by dividing each point in the off-line bandpasses by the average of each pair of on-line points around those off-line points. We find that the colour between the bluest bandpass and the on-line bandpass is consistent with zero, with a mean value of 6.30 ± (computed following the method described in Section 3). The mean colour of the nm and on-line bandpasses is 3.57 ± , and the mean colour between the reddest and on-line bandpasses is 8.99 ± We also present the standard deviation of each colour for a number of binning factors in Fig. 13. We find that the trend for each colour Table 7. Time-averaged flux ratios and noise estimates (outlying absolute fluxes excluded). λ E (nm) λ P (nm) λ S (nm) δf/f σ δf/f σ w σ r β In-transit Out-of-transit Note. Same as in Table 6, but the flux ratios listed here are those computed after excluding outlying absolute flux measurements from the analysis.